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Effects of Comprehensive Stroke Care Capabilities on In-Hospital Mortality of Patients with Ischemic andHemorrhagic Stroke: J-ASPECT Study

Koji Iihara1*, Kunihiro Nishimura2, Akiko Kada3, Jyoji Nakagawara4, Kuniaki Ogasawara5, Junichi Ono6,

Yoshiaki Shiokawa7

, Toru Aruga8

, Shigeru Miyachi9

, Izumi Nagata10

, Kazunori Toyoda11

,Shinya Matsuda12, Yoshihiro Miyamoto2, Akifumi Suzuki13, Koichi B. Ishikawa14, Hiroharu Kataoka15,

Fumiaki Nakamura16, Satoru Kamitani16

1 Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan, 2 Department of Preventive Medicine and Epidemiologic

Informatics, National Cerebral and Cardiovascular Center, Suita, Japan, 3 Clinical Research Center, National Hospital Organization, Nagoya Medical Center, Nagoya, Japan,

4 Integrative Stroke Imaging Center, National Cerebral and Cardiovascular Center, Suita, Japan, 5 Department of Neurosurgery, Iwate Medical University, Morioka, Japan,

6 Chiba Cardiovascular Center, Ichihara, Japan, 7 Department of Neurosurgery, Kyorin University, Mitaka, Japan,8 Showa University Hospital, Tokyo, Japan,9 Department

of Neurosurgery, Nagoya University, Nagoya, Japan,10 Department of Neurosurgery, Nagasaki University, Nagasaki, Japan, 11 Department of Cerebrovascular Medicine,

National Cerebral and Cardiovascular Center, Suita, Japan, 12 Department of Preventive Medicine and Community Health, University of Occupational and Environmental

Health, Kita-Kyushu, Japan,13 Research Institute for Brain and Blood Vessels, Akita, Japan,14 Center for Cancer Control and Information Services, National Cancer Center,

Tokyo, Japan,15 Department of Neurosurgery, National Cerebral and Cardiovascular Center, Suita, Japan,16 Department of Public Health, The University of Tokyo, Tokyo,

Japan

AbstractBackground:The effectiveness of comprehensive stroke center (CSC) capabilities on stroke mortality remains uncertain. Weperformed a nationwide study to examine whether CSC capabilities influenced in-hospital mortality of patients withischemic and hemorrhagic stroke.

Methods and Results: Of the 1,369 certified training institutions in Japan, 749 hospitals responded to a questionnairesurvey regarding CSC capabilities that queried the availability of personnel, diagnostic techniques, specific expertise,infrastructure, and educational components recommended for CSCs. Among the institutions that responded, data onpatients hospitalized for stroke between April 1, 2010 and March 31, 2011 were obtained from the Japanese DiagnosisProcedure Combination database. In-hospital mortality was analyzed using hierarchical logistic regression analysis adjustedfor age, sex, level of consciousness on admission, comorbidities, and the number of fulfilled CSC items in each componentand in total. Data from 265 institutions and 53,170 emergency-hospitalized patients were analyzed. Mortality rates were7.8% for patients with ischemic stroke, 16.8% for patients with intracerebral hemorrhage (ICH), and 28.1% for patients withsubarachnoid hemorrhage (SAH). Mortality adjusted for age, sex, and level of consciousness was significantly correlated withpersonnel, infrastructural, educational, and total CSC scores in patients with ischemic stroke. Mortality was significantly

correlated with diagnostic, educational, and total CSC scores in patients with ICH and with specific expertise, infrastructural,educational, and total CSC scores in patients with SAH.

Conclusions:CSC capabilities were associated with reduced in-hospital mortality rates, and relevant aspects of care werefound to be dependent on stroke type.

Citation: Iihara K, Nishimura K, Kada A, Nakagawara J, Ogasawara K, et al. (2014) Effects of Comprehensive Stroke Care Capabilities on In-Hospital Mortality ofPatients with Ischemic and Hemorrhagic Stroke: J-ASPECT Study. PLoS ONE 9(5): e96819. doi:10.1371/journal.pone.0096819

Editor:Hooman Kamel, Weill Cornell Medical College, United States of America

ReceivedNovember 4, 2013; Accepted April 11, 2014; Published May 14, 2014

Copyright: 2014 Iihara et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding:This study was supported by Grants-in-Aid from the Ministry of Health, Labour, and Welfare of Japan (Principal Investigator: Koji Iihara). The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests:Ube Industries, Ltd., Central Hospital participated in this study by providing survey data. This does not alter the authors adherence toPLOS ONE Editorial policies and criteria.

* E-mail: [email protected]

Introduction

In Japan, stroke is the third-leading cause of death, as well as a

leading cause of long-term disability. Almost 270,000 individuals

in Japan have a new or recurrent stroke each year, and nearly

120,000 individuals die following a stroke [1]. In 2000, the Brain

Attack Coalition discussed the concept of stroke centers and

proposed two types of centers: comprehensive [2] and primary [3].

Most patients with stroke can be appropriately treated at a

primary stroke center (PSC), and the Joint Commission has

established programs for certifying PSCs and measuring their

performance [4]. The concept and recommended key components

of comprehensive stroke centers (CSCs) enable intensive care and

specialized techniques that are not available at most PSCs [2,5].

PLOS ONE | www.plosone.org 1 May 2014 | Volume 9 | Issue 5 | e96819
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Although stroke performance measures have been developed to

monitor and improve quality of care, a substantial proportion of

patients do not receive effective treatments, and population-based

studies have been called for to evaluate the successful translation of

evidence-based medicine into clinical practice [4] Organized

stroke unit care is a form of in-hospital care provided by nurses,

doctors, and therapists who work as a coordinated team

specialized in caring for patients with stroke [6]. The effectiveness

of organized stroke care has been reported for different ischemic

stroke subtypes in the organized care index (OCI) using data from

the Registry of the Canadian Stroke Network [7,8]. However, the

effectiveness of CSC capabilities on the mortality of patients with

ischemic and hemorrhagic stroke remains uncertain. In this study,

we examined whether CSC capabilities influence in-hospitalmortality for all types of stroke in a real-world setting by using

data from the J-ASPECT nationwide stroke registry (obtained

from the Japanese Diagnosis Procedure Combination [DPC]-

based Payment System) [9].

Methods

Of the 1,369 certified training institutions of the Japan

Neurosurgical Society, the Japanese Society of Neurology, and/

or the Japan Stroke Society, 749 hospitals responded to a

questionnaire survey regarding CSC capabilities. The CSC

capabilities were assessed using 25 items specifically recommended

for CSCs [2] that were divided into 5 components regarding (1)

personnel (seven items: board-certified neurologists, board-certi-

fied neurosurgeons, board-certified endovascular physicians,

board-certified physicians in critical care medicine, board-certified

physicians in physical medicine and rehabilitation, personnel in

rehabilitation therapy, and stroke rehabilitation nurses), (2)

diagnostic techniques (six items: 24 hours/day, 7 days/week

[24/7] availability of computed tomography [CT], magnetic

resonance imaging [MRI] with diffusion-weighted imaging, digital

cerebral angiography, CT angiography, carotid duplex ultra-

sound, and transcranial Doppler), (3) specific expertise (five items:

carotid endarterectomy, clipping of intracranial aneurysms [IAs],

removal of intracerebral hemorrhage [ICH], coiling of IAs, andintra-arterial reperfusion therapy), (4) infrastructure (five items:

stroke unit, intensive care unit, operating room staffed 24/7,

interventional services coverage 24/7, and stroke registry), and (5)

educational components (two items: community education and

professional education). A score of 1 point was assigned if the

hospital met each recommended item, yielding a total CSC score

of up to 25. The scores were also summed for each component

(subcategory CSC score). The impact of specific aspects of acute

stroke care (monitoring, early rehabilitation, admission to stroke

care unit [SCU], acute stroke team, the organized stroke care

index [7], existence of a tissue plasminogen activator [t-PA]

Table 1.Number and percentage of participating hospitals (n = 265) with the recommended items of comprehensive stroke carecapabilities.

Components Items n %

Personnel Neurologists 143 54.0

Neurosurgeons 251 94.7

Endovascular physicians 118 44.5Critical care medicine 65 24.5

Physical medicine and rehabilitation 42 15.8

Rehabilitation therapy 265 100

Stroke rehabilitation nurses 38 14.6

Diagnostic techniques CT 264 99.6

MRI with diffusion 237 89.4

Digital cerebral angiography 226 85.6

CT angiography 234 88.3

Carotid duplex ultrasound 102 38.5

TCD 53 20.2

Specific expertise Carotid endarterectomy 231 87.2

Clipping of intracranial aneurysm 250 94.3

Hematoma removal/draining 253 95.5

Coiling of intracranial aneurysm 153 57.7

Intra-arterial reperfusion therapy 199 75.1

Infrastructure Stroke unit 55 20.8

Intensive care unit 169 63.8

Operating room staffed 24/7 185 70.0

Interventional services coverage 24/7 122 46.0

Stroke registry 109 41.8

Education Community education 147 55.7

Professional education 171 64.8

CT, computed tomography; MRI, magnetic resonance imaging; TCD, transcranial Doppler.doi:10.1371/journal.pone.0096819.t001

Effects of Comprehensive Stroke Care on Mortality


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protocol, number of t-PA cases/year, and number of acute stroke

cases/year) on stroke mortality was also examined. This survey

was completed by neurosurgeons or neurologists in the responding

hospitals and returned by mail. Any incomplete answers were

completed in follow-up phone interviews with the neurosurgeons

or neurologists of the study group. The English version of the

survey is shown in File S1.

This cross-sectional survey used the DPC discharge database

from participating institutions in the J-ASPECT Study. The DPC

is a mixed case patient classification system that was launched in

2002 by the Ministry of Health, Labor, and Welfare of Japan and

was linked with a lump-sum payment system [9]. Of the 749

hospitals that responded to the institutional survey regarding CSC

capabilities, 265 agreed to participate in the DPC discharge

database study (File S2). Computer software was developed to

identify patients hospitalized because of acute stroke from the

annual de-identified discharge database by using the InternationalClassification of Diseases (ICD)-10 diagnosis codes related to

ischemic stroke (I63.0-9), nontraumatic ICH (ICH: I61.0-9, I62.0-

1, and I62.9), and subarachnoid hemorrhage (SAH: I60.0-9).

Because of major differences in their typical prognosis, patients

with transient ischemic attack were excluded. Patients hospitalized

because of ischemic and hemorrhagic stroke between April 1, 2010

and March 31, 2011 were included; however, patients with

scheduled admissions were excluded from analysis. The following

data were collected from the database: unique identifiers of

hospitals, patients age and sex, diagnoses, comorbidities at

admission, in-hospital use of medications (antihypertensive agents,

oral hypoglycemic agents, insulin, antihyperlipidemic agents,

statins, anticoagulant agents, or antiplatelet agents), smoking,

arrival by ambulance or not, level of consciousness at admission

according to the Japan Coma Scale [10], and discharge status.

The Japan Coma Scale [11] was originally published in 1974, the

same year as the Glasgow Coma Scale (GCS) [12], and it remains

one of the most popular grading scales for assessing impaired

consciousness among health care professionals and personnel for

emergency medical services in Japan. Grading with the 1-, 2-, and

3-digit codes corresponds to the following statuses: 1) the patient is

awake in the absence of any stimulation, 2) the patient can be

aroused but reverts to the previous state after the cessation of

stimulation, and 3) the patient cannot be aroused even by forceful

mechanical stimulation. Each specific digit status is further

subdivided into three levels: 1-digit code into 1, 2, and 3; 2-digit

code into 10, 20, and 30; and 3-digit code into 100, 200, and 300

(Table S1). In addition to these nine grades, a normal level ofconsciousness is graded as zero. Consciousness level on admission

was determined by the physician and data on all medication use

was collected electronically from the claim data. Comorbidity was

determined primarily from the ICD-10 code, but was also checked

against what medications and procedures the patient was

receiving/undergoing, to see if these were compatible with the

code data. Smoking was defined by the physicians record, which

rated patients as active or inactive smokers. In-hospital mortality,

defined as death by the time of discharge from the hospital, was

analyzed with the total and subcategory CSC scores using

hierarchical logistic regression analysis adjusted for age, sex,

Table 2.Demographics of the study cohort according to the Diagnosis Procedure Combination (DPC) discharge database study ina comparison of hospitals that agreed to participate in the present study and those that did not.

Participating hp Non-participating hp P value#

(n = 265) (n = 484)

Hospital characteristics (CSC scores)

Total score (25 items) 15.464.2 13.564.6 ,0.001Personnel (7 items) 3.561.2 3.161.3 ,0.001

Diagnostic techniques (6 items) 4.261.2 3.961.3 0.002

Specific expertise (5 items) 4.061.4 3.661.6 ,0.001

Infrastructure (5 items) 2.461.4 1.961.4 ,0.001

Education (2 items) 1.260.8 1.060.8 0.002

Number of beds, n (%)

2049 3 (1.1) 13 (2.7) ,0.001

5099 9 (3.4) 21 (4.3)

100299 66 (24.9) 166 (34.3)

300499 97 (36.6) 163 (33.7)

500 90 (34.0) 117 (24.2)

Annual stroke cases, n (%)

049 8 (3.0) 43 (8.9) 0.003

5099 31 (11.7) 47 (9.7)

100199 56 (21.1) 143 (29.5)

200299 67 (25.3) 88 (18.2)

300 92 (34.7) 136 (28.1)

Annual volume of t-PA infusion 8.3 6.4 0.002

#Wilcoxon rank-sum test.CSC, comprehensive stroke center.Hp, hospital.doi:10.1371/journal.pone.0096819.t002



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Japan Coma Scale score, comorbidities, and institutional differ-

ence.

Ethics StatementThis research plan was designed by the authors and approved

by the Institutional Review Board of the National Cerebral and

Cardiovascular Center, which waived the requirement for

individual informed consent.

Statistical AnalysisWe used hierarchical logistic regression models [13,14] to

estimate odds ratios (ORs) for in-hospital mortality. Each model

had two levels of hierarchy (hospital and patient) while considering

the random effects of hospital variation, as well as fixed effects of

CSC score and patient effects of age, sex, and level of

consciousness. The total score and each subcategory score were

analyzed separately. We also divided CSC score into quintiles and

analyzed the trend with the Cochran-Armitage trend test. The

Table 3.Demographics of the patient study cohort at the time of diagnosis and hospital characteristics according to stroke type.

Total Ischemic Stroke

Intracerebral

hemorrhage

Subarachnoid

hemorrhage

(n = 53,170) (n = 32,671) (n = 15,699) (n = 4,934)

Male, n (%) 29,353 (55.2) 18,816 (57.6) 9,030 (57.5) 1,584 (32.1)

Age, mean years6

SD 72.56

13.1 74.46

12.2 70.76

13.5 64.76

14.8Hypertension, n (%) 39,918 (75.1) 22,531 (69.0) 13,281 (84.6) 4,229 (85.7)

Diabetes Mellitus, n (%) 13,725 (25.8) 9,318 (28.5) 3,278 (20.9) 1,174 (23.8)

Hyperlipidemia, n (%) 15,015 (28.2) 11,104 (34.0) 2,529 (16.1) 1,412 (28.6)

Smoking (n = 4,4842) 12,761 (24.0) 8,188 (25.1) 3,540 (22.5) 1,074 (21.8)

Medications during hospitalization

Antihypertensive agent 34,136 (64.2) 17,694 (54.2) 12,537 (79.9) 4,019 (81.5)

Anti-renin-angiotensin system agent 19,881 (37.4) 10,262 (31.4) 8,280 (52.7) 1,410 (28.6)

Ca channel antagonist 25,984 (48.9) 10,469 (32.0) 11,719 (74.6) 3,903 (79.1)

Sympathetic antagonist 6,334 (11.9) 3,821 (11.7) 2,172 (13.8) 364 (7.4)

*b-blocker,a,b-blocker 4,357 (8.2) 3,048 (9.3) 1,133 (7.2) 188 (3.8)

a-blocker 2,374 (4.5) 953 (2.9) 1,232 (7.8) 200 (4.1)

Diuretic agent 9,950 (18.7) 5,860 (17.9) 3,074 (19.6) 1,049 (21.3)

Loop diuretic 7,434 (14.0) 4,609 (14.1) 1,912 (12.2) 940 (19.1)

Other diuretic 4,425 (8.3) 2,527 (7.7) 1,653 (10.5) 255 (5.2)

Antidiabetic agent 10,295 (19.4) 6,784 (20.8) 2,473 (15.8) 1,075 (21.8)

Insulin 7,654 (14.4) 4,597 (14.1) 2,044 (13.0) 1,046 (21.2)

Oral antidiabetic agent 5,749 (10.8) 4,459 (13.6) 1,110 (7.1) 197 (4.0)

Antihyperlipidemic agent 12,387 (23.3) 9,264 (28.4) 1,839 (11.7) 1,310 (26.6)

Statin 10,099 (19.0) 7,840 (24.0) 1,366 (8.7) 912 (18.5)

Antiplatelet agent 23,635 (44.5) 21,746 (66.6) 625 (4.0) 1,298 (26.3)

Aspirin 11,929 (22.4) 11,119 (34.0) 378 (2.4) 447 (9.1)

Japan Coma Scale

0, n (%) 19,635 (36.9) 15,027 (46.0) 3,620 (23.1) 1,024 (20.8)

1-digit code, n (%) 19,371 (36.4) 12,375 (37.9) 5,934 (37.8) 1,117 (22.6)

2-digit code, n (%) 6,937 (13.0) 3,396 (10.4) 2,705 (17.2) 852 (17.3)

3-digit code, n (%) 7,227 (13.6) 1,873 (5.7) 3,440 (21.9) 1,941 (39.3)

Emergency admission by ambulance, n (%) 31,995 (60.2) 17,336 (53.1) 10,909 (69.5) 3,830 (77.6)

Average days in hospital (range) 21 (1140) 20 (1238) 22 (1043) 30 (1254)

Hospital characteristics (CSC scores)

Total score (25 items) 16.763.8 16.863.4 17.163.4

Personnel (7 items) 3.761.2 3.761.2 3.861.2

Diagnostic techniques (6 items) 4.461.1 4.561.0 4.561.0

Specific expertise (5 items) 4.461.0 4.460.9 4.560.8

Infrastructure (5 items) 2.861.3 2.961.3 2.961.3

Education (2 items) 1.460.8 1.460.8 1.460.8

CSC, comprehensive stroke center.

*A composite variable with a pure beta antagonist and a mixed alpha/beta adrenergic antagonist (e.g., labetalol).doi:10.1371/journal.pone.0096819.t003



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difference between participating and non-participating hospitals in

the DPC discharge study was determined by Wilcoxon rank-sum

test. The analyses were performed using SAS version 9.2 (SAS

Institute Inc., Cary, NC, USA) and STATA version 12 (STATA

Corp, College Station, TX, USA).

Results

A total of 265 hospitals participated in this study. The number

and percentage of the participating hospitals with the recom-

mended items of CSC capabilities are shown in Table 1. The

distribution of total CSC scores ranged from 1 to 23 (mean: 15.4,

median: 14 standard deviation [SD]: 4.2, interquartile range

[IQR]: 1118). Because we initially sent the CSC questionnaire to

749 hospitals, we sought to determine whether there was a

selection bias in stroke care capabilities that could have impacted

which hospitals returned the questionnaire. We found that such a

bias did exist; in fact, the total CSC scores, subcategory CSC

scores and annual volume of t-PA infusion, with the exception of

the diagnostic techniques and education/research subcategories,were significantly higher for the participating hospitals than for the

non-participating hospitals (Table 2).

Data from 265 institutions and 53,170 emergency-hospitalized

patients (age in years, mean 6SD: 72.5613.1; male: 55.2%) were

analyzed. Patient demographics according to stroke type at the

time of diagnosis are shown in Table 3. The study cohort included

32,671 patients with ischemic stroke (age: 74.4612.2 years; male:

57.6%), 15,699 with ICH (age: 70.7613.5 years; male: 57.5%),

and 4,934 with SAH (age: 64.7614.8 years; male: 32.1%). Use of

antihypertensive agents, antidiabetic agents, antihyperlipidemic

agents, and antiplatelet agents is also shown in Table 3. Almost

60% of the patients arrived by ambulance, with the incidenceranging from 77.6% for SAH to 53.1% for ischemic stroke. These

rates of arrival by ambulance based on stroke type were in

accordance with different degrees of stroke severity, as reflected by

level of consciousness. Hospital characteristics shown by total and

subcategory CSC scores did not reveal any significant differences

with respect to stroke type.

Overall, mortality rates were 7.8% for ischemic stroke, 16.8%

for ICH, and 28.1% for SAH. Table 46 show the results of a

hierarchical logistic regression analysis of these data. Mortality of

patients with ischemic stroke was significantly correlated with male

sex (OR = 1.23), age (10 incremental years, OR= 1.4), and level of

consciousness (1-digit code: OR = 2.4, 2-digit code: OR = 7.46, 3-

digit code: OR = 21.62, versus zero [normal consciousness

{control}]) as patient characteristics, and total CSC score

(OR = 0.97) adjusted for age, sex, and level of consciousness as ahospital characteristic (Table 4). Mortality of patients with ICH

was also significantly correlated with male sex (OR = 1.72), age (10

incremental years, OR = 1.36), and level of consciousness (1-digit

code: OR= 1.45, 2-digit code: OR= 4.22, 3-digit code:

OR = 49.59, versus zero as control) as patient characteristics and

total CSC score (OR = 0.97) adjusted for age, sex, and level of

consciousness as a hospital characteristic (Table 5). Mortality of

Table 4.The impact of total comprehensive stroke care (CSC) score on in-hospital mortality after ischemic stroke, adjusted by age,sex, and level of consciousness at admission according to the Japan Coma Scale (JCS).

Factor OR 95% CI P value

Male 1.23 1.121.35 ,0.001

Age 1.40 1.341.47 ,0.001

CSC total score 0.97 0.960.99 0.001JCS

normal 1

one-digit code 2.40 2.112.74 ,0.001

two-digit code 7.46 6.478.60 ,0.001

three-digit code 21.62 18.6925.02 ,0.001

CI, confidence interval; CSC, comprehensive stroke care; JCS, Japan Coma Scale; OR, odds ratio.doi:10.1371/journal.pone.0096819.t004

Table 5. The impact of total comprehensive stroke care (CSC) score on in-hospital mortality after intracerebral hemorrhage,adjusted by age, sex, and level of consciousness at admission according to the Japan Coma Scale (JCS).

Factor OR 95% CI P value

Male 1.72 1.541.92 ,0.001

Age 1.36 1.301.42 ,0.001

CSC total score 0.97 0.950.99 0.003

JCS

normal 1

one-digit code 1.45 1.141.83 0.002

two-digit code 4.22 3.345.33 ,0.001

three-digit code 49.59 40.1261.27 ,0.001




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patients with SAH was likewise significantly correlated with male

sex (OR = 1.39), age (10 incremental years, OR = 1.37), and level

of consciousness (2-digit code: OR= 2.01, 3-digit code:

OR = 17.12, versus zero as control) as patient characteristics and

total CSC score (OR = 0.95) adjusted for age, sex, and level ofconsciousness as a hospital characteristic. Therefore, total CSC

score was independently associated with in-hospital mortality for

all stroke types after adjusting for age, sex, and stroke severity

(Table 6). The impact of total CSC score on in-hospital mortality

for ischemic stroke and ICH remained significant after adjustment

for age, sex, severity of stroke, and existence of comorbid

conditions (hypertension, diabetes mellitus, and hyperlipidemia)

(Table S2S4).

Table 79 show the correlations between CSC subcategory

scores and in-hospital mortality adjusted for age, sex, and level of

consciousness depending on the different stroke types: mortality of

patients with ischemic stroke was significantly correlated with

subcategory scores in personnel (OR = 0.93), infrastructure

(OR = 0.94), and education (OR = 0.89) (Table 7). Mortality of

patients with ICH was significantly correlated with subcategory

scores in diagnostic technique (OR = 0.91), infrastructure

(OR = 0.92), and education (OR = 0.91) (Table 8). Mortality of

patients with SAH was significantly associated with subcategory

scores in personnel (OR= 0.91) specific expertise (OR = 0.83),

infrastructure (OR = 0.89), and education (OR = 0.84) (Table 9).

We found that while infrastructure and education subcategory

CSC scores significantly impacted outcomes for all types of stroke,

other subcategory CSC scores were differentially associated with

in-hospital mortality depending on stroke type.

Figure 1 shows the impact of total CSC score classified into

quintiles (Q1: 412, Q2: 1314, Q3: 1517, Q4: 18, Q5: 1923)

on the in-hospital mortality of patients with all types of stroke (a),

ischemic stroke (b), ICH (c), and SAH (d) after adjusting for age,

sex and level of consciousness. There was a significant association

between total CSC score and in-hospital mortality in all types of

stroke (all P,

0.001) (Table 46). Figure 2 illustrates the impact oftotal CSC score on the in-hospital mortality of patients with all

types of stroke (a), ischemic stroke (b), ICH (c), and SAH (d) after

adjustment for age; sex; level of consciousness; and incidence of

hypertension, hyperlipidemia, and diabetes mellitus. The associ-

ation between total CSC score and in-hospital mortality in patients

after all types of stroke (a), ischemic stroke (b), and ICH (c)

remained significant after adjustment for age; sex; level of

consciousness; and incidence of hypertension, hyperlipidemia,

and diabetes mellitus. This same association was not evident in

patients with SAH (P = 0.601) (Table 10).

Hospitals with higher CSC scores were also more likely to

provide early rehabilitation, improved monitoring, the possibility

of admission to an SCU, presence of an acute stroke care team,

existence of a t-PA protocol, greater numbers of t-PA cases/year,

and higher scores on the organized stroke care index. In addition

to the CSC score, the processes of acute stroke care, such as

admission to SCU, presence of an acute stroke team, the organized

stroke care index [7], and number of acute stroke cases/staff

physician significantly impacted in-hospital mortality after all types

of acute stroke, although in some cases, to a greater or lesser

degree for the different types of stroke (Table 1114).

Discussion

Using the nationwide discharge data obtained from the

Japanese DPC-based Payment System, we evaluated the effect of

Table 6. The impact of total comprehensive stroke care (CSC) score on in-hospital mortality after subarachnoid hemorrhage,adjusted by age, sex, and level of consciousness at admission according to the Japan Coma Scale (JCS).

Factor OR 95%CI P value

Male 1.39 1.171.65 ,0.001

Age 1.37 1.291.45 ,0.001

CSC total score 0.95 0.930.98 ,

0.001JCS

normal 1

one-digit code 1.05 0.751.46 0.785

two-digit code 2.01 1.462.77 ,0.001

three-digit code 17.13 13.1422.35 ,0.001


Table 7. The impact of subcategory CSC score on in-hospital mortality after ischemic stroke adjusted by age, sex and JCS.

Component OR 95% CI P value

Personnel 0.93 0.880.98 0.008

Diagnostic techniques 0.95 0.901.01 0.090

Specific expertise 0.96 0.901.01 0.136

Infrastructure 0.94 0.900.99 0.014

Education/research 0.89 0.830.96 0.003




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hospital characteristics based on the recommended components of

CSCs [2] on the in-hospital mortality of patients with acute

ischemic and hemorrhagic stroke treated between April 1, 2010

and March 31, 2011. We found that the total CSC score was

significantly associated with in-hospital mortality rates irrespective

of stroke type after adjustment for age, sex, and initial level of

consciousness according to the Japan Coma Scale. However, the

subcategory scores that were significantly associated with in-

hospital mortality differed among stroke type. Importantly, theassociation between total CSC scores and in-hospital mortality

remained significant after adjustment for age; sex; initial level of

consciousness according to the Japan Coma Scale; and incidence

of hypertension, diabetes mellitus and hyperlipidemia for all types

of stroke except SAH. These findings highlight the importance of

CSC capabilities for optimal treatment of ischemic and hemor-

rhagic stroke and will enable health care professionals and policy

makers to focus their efforts on improving specific aspects of CSC

capabilities for different types of stroke.

Increasing attention has been given to defining the quality and

value of health care through the reporting of process and outcome

measures. Following the original proposal to establish CSCs [2],

detailed metrics for measuring quality of care in CSCs have been

reported [5]. The so-called drip-and-ship model has emerged asa paradigm for emergency departments that are able to diagnose

acute ischemic stroke and administer intravenous (IV) recombi-

nant t-PA (rt-PA) but lack the infrastructure to provide intensive

monitoring for patients after rt-PA administration [15,16]. A

recent study demonstrated that despite having more severe strokes

on arrival at the CSC, transfer-in patients with acute ischemic

stroke had in-hospital mortality similar to that of front door

patients and were more likely to be discharged to rehabilitation.

These findings lend support to the concept of regionalized stroke

care and directing patients with greater disability to more

advanced stroke centers [17]. At present, no official certification

of stroke centers in Japan has been launched, and the current

study indicates that patients with acute ischemic stroke or

hemorrhagic stroke are being admitted on an emergent basis to

hospitals with similar CSC total and subcategory scores.

In the present study, stroke severity was adjusted by baseline

level of consciousness according to the Japan Coma Scale [10,11].

The Get With the Guidelines-Stroke (GWTG-Stroke) risk model

was recently developed to predict in-hospital ischemic stroke

mortality, suggesting that the National Institutes of Health StrokeScale (NIHSS) score provides substantial incremental information

on a patients mortality risk [18], emphasizing the importance of

adjustment of stroke severity to develop a hospital risk model for

mortality [19]. Previous prospective multicenter study has

demonstrated that the development of a decreased level of

consciousness within the initial hours after stroke onset, as

evaluated by a simple six-point scale, is a powerful independent

predictor of mortality after a major ischemic stroke of the anterior

vasculature [20]. In hemorrhagic stroke, the degree of impaired

consciousness at admission was also included in the various

proposed ICH scores to predict functional outcome and mortality

[21,22]. This study demonstrated that the level of consciousness at

admission, as measured by the Japan Coma Scale, is a powerful

independent predictor of mortality after ischemic and hemorrhag-ic stroke. Determining an individual patients risk of mortality at

admission could improve clinical care by providing valuable

information to patients and their family members and by

identifying those at high risk for poor outcomes who may require

more intensive resources.

Health care quality of CSCs in the present study was scored on

the basis of the results of a questionnaire referring to 25 items

originally recommended by the Brain Attack Coalition. Although

there is now increasingly good evidence from initiatives like

GWTG-Stroke [23] that a process based on the systematic

collection and evaluation of stroke performance measures can

Table 8.The impact of subcategory CSC score on in-hospital mortality after intracerebral hemorrhage adjusted by age, sex andJCS.


Personnel 0.98 0.921.04 0.523


Specific expertise 0.93 0.861.00 0.055Infrastructure 0.92 0.870.98 0.005



Table 9.The impact of subcategory CSC score on in-hospital mortality after subarachnoid hemorrhage adjusted by age, sex and

JCS.


Personnel 0.91 0.840.98 0.016


Specific expertise 0.83 0.750.93 ,0.001

Infrastructure 0.89 0.830.96 0.002





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rapidly improve the quality of stroke care delivered by hospitals,

current metrics are mostly limited to process measures that address

the care of patients with ischemic stroke in acute hospital-based

settings [4]. In addition, there is a pressing need to demonstrate a

direct link between better adherence to stroke performance

measures and improved patient-oriented outcomes [4,24].

One potential issue with the interpretation of this study could be

the lack of a control group. Although there is currently no clear

consensus regarding the recommended criteria for CSCs in Japan,

the present study distinctly shows that the CSC scores widelydistributed in Figure 1 and classified into quintiles were

significantly associated with in-hospital mortality for all types of

stroke; in fact, mortality after all types of stroke markedly

decreased, for example, in ischemic stroke cases by about 40%

in hospitals in the highest quintile compared with those in the

lowest quintile.

In the present study, our questionnaire was primarily based on

the American definition of CSCs. However, according to the

definitions derived from a European survey of experts in the field

[25], facilities that meet the criteria for CSCs should include the

capability to conduct sophisticated monitoring, such as automated

electrocardiography (ECG) monitoring at bedside and automated

monitoring of pulse oximetry, in addition to the numerous aspects

of care capability indexed by the American definition of CSCs

used in this study. According to the European approach, to meet

the criteria for CSCs, hospitals should have the availability of at

least 80% of the components rated as absolutely necessary by at

least 50% of experts who participated in the previous expert

survey; moreover, these components must be present in each of 6

categories and include the 19 components rated as absolutely

necessary by .75% of experts. Based on the present results and anadditional ongoing study using a validation cohort in Japan, the

criteria for the designation of CSCs in Japan should be determined

after further thorough discussion among Japanese stroke experts.

The present study demonstrated the feasibility and impact of

using nationwide discharge data with hierarchical logistic regres-

sion analysis to examine the random effects that vary among

hospitals, as well as the fixed effects of CSC score and patient

effects of age, sex, and level of consciousness. We used unique

hospital ID in random-intercept hierarchical regression models to

assess the association between CSC score and mortality, adjusting

Figure 1. Associations between total comprehensive stroke care (CSC) scores separated into quintiles (Q1: 412, Q2: 1314, Q3: 1517, Q4: 18, Q5: 1923) and in-hospital mortality of patients after all types of stroke (a), ischemic stroke (b), intracerebralhemorrhage (ICH) (c), and subarachnoid hemorrhage (SAH) (d), after adjustment for age and sex.Odds ratios (ORs) and 95% confidenceintervals (CIs) of in-hospital mortality of each total CSC score quintile are depicted compared with that of Q1 as control.doi:10.1371/journal.pone.0096819.g001



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for patient characteristics and the hospital where a patient was

treated.

This model adjusts for hospital-level effects that arise from

factors such as geographical location and ageing of the local

population. After adjustment, we can isolate the pure CSC score

effects on mortality by hospital, as discussed by Localio et al. [26].

If the CSC score is no longer significant after accounting for

hospital-level variation, the differences in mortality can be

assumed to arise from differences among hospitals. This approachenabled us to elucidate the impact of various CSC metrics on in-

hospital mortality of patients with different stroke types. By

expanding the scope of performance measures to include all types

of stroke, the present study was able to direct links between specific

recommended items of CSC capacities and in-hospital mortality

after both hemorrhagic and ischemic stroke. While previous

reports [7] showed that aspects of acute stroke care, such as

admission to an SCU, the presence of an acute stroke team, and

the organized stroke care index, were significantly associated with

effects on in-hospital mortality after acute stroke, the present study

clearly shows that the same is true for the CSC score based on the

items recommended by the American Stroke Association.

Finally, one could argue that there really is no concept of 3/4

CSCs, but rather only CSCs or PSCs. In light of the existing

evidence regarding the impact of the recommended CSC items on

stroke outcomes, we advocate a CSC scoring system to examine

the impact of availability of the recommended items on in-hospital

mortality for all types of stroke. Considering the marked impact of

the CSC score on outcome after all types of stroke, the differentialimpacts of CSC subcategory scores for different stroke types may

make a single simple and effective CSC criterion unrealistic as a

tool to produce a nationwide reduction in stroke mortality. In our

opinion, it may be a more viable option to employ CSC scores in a

more limited fashion, that is, to benchmark the state of care

currently provided by medical centers treating stroke patients.

LimitationsFirst, the questionnaire used in this study is new and has not

undergone pilot testing or systematic analysis; thus, its validity and

reliability are uncertain. The current set of CSC score items does

Figure 2. Associations between total comprehensive stroke care (CSC) scores separated into quintiles (Q1: 412, Q2: 1314, Q3: 1517, Q4: 18, Q5: 1923) and in-hospital mortality of patients after all types of stroke (a), ischemic stroke (b), intracerebralhemorrhage (ICH) (c), and subarachnoid hemorrhage (SAH) (d), after adjustment for age; sex; initial level of consciousness; andincidence of hypertension, hyperlipidemia, and diabetes mellitus. Odds ratios (ORs) and 95% confidence intervals (CIs) of the in-hospitalmortality of each total CSC score quintile are depicted compared with that of Q1 as control.doi:10.1371/journal.pone.0096819.g002



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not include all worthwhile items related to CSC. These items were

appropriately modified from the original American version [2] in

consideration of the medical, social, and logistical differences

between the U.S. and Japan. For example, most cerebrovascularsurgeries, including carotid endarterectomy and neurointerven-

tion, are performed by neurosurgeons rather than vascular

surgeons or neuroradiologists. At the beginning of this project, a

survey including the 25 components recommended by the Brain

Attack Coalition in 2005 was created after a review of the

literature on comprehensive stroke centers and a thorough

discussion by an expert panel. Some recommended items such

as availability of ventriculostomy were excluded from our

questionnaire merely for simplicity, and thus to increase the

response rate of the survey, since they seemed to be identical torecommendations of the board-certified neurosurgeons of Japan.

On the other hand, some items such as transesophageal

echocardiography were excluded because of the expected very

low usage of this examination. According to the Japanese Stroke

Databank 2009, for example, transesophageal echocardiography

was performed for only 5.4% of the 34,417 acute ischemic stroke

Table 10. Associations between total comprehensive stroke care (CSC) scores separated into quintiles (Q1: 412, Q2: 1314, Q3:1517, Q4: 18, Q5: 1923) and in-hospital mortality of patients after all types of stroke (a), ischemic stroke (b), intracerebralhemorrhage (ICH) (c), and subarachnoid hemorrhage (SAH) (d), model 1: after adjustment for age, sex, and initial level ofconsciousness; and model 2: after adjustment for age, sex, initial level of consciousness, and incidence of hypertension,hyperlipidemia, and diabetes mellitus.

Model 1 Model 2

Type of Stroke Quintile OR P value 95% CI P for trend OR P value 95% CI P for trend

Whole Population(n = 53,170)

Q2 0.87 0.077 0.74 1.02 0.005 0.88 0.119 0.75 1.03 0.013

Q3 0.84 0.023 0.72 0.98 0.86 0.045 0.74 1.00

Q4 0.87 0.115 0.74 1.03 0.91 0.254 0.77 1.07

Q5 0.73 0.003 0.60 0.90 0.74 0.004 0.60 0.91

Ischemic Stroke(n = 32,671)

Q2 0.90 0.278 0.75 1.08 0.003 0.92 0.356 0.77 1.10 0.005

Q3 0.79 0.008 0.66 0.94 0.81 0.015 0.68 0.96

Q4 0.84 0.097 0.69 1.03 0.86 0.131 0.71 1.05

Q5 0.71 0.006 0.56 0.91 0.73 0.01 0.58 0.93

ICH (n = 15,699) Q2 0.76 0.015 0.62 0.95 ,0.001 0.79 0.034 0.63 0.98 0.053

Q3 0.82 0.058 0.67 1.01 0.83 0.083 0.68 1.02

Q4 0.79 0.039 0.63 0.99 0.82 0.099 0.65 1.04

Q5 0.76 0.050 0.58 1.00 0.76 0.051 0.58 1.00

SAH (n = 4,934) Q2 1.04 0.814 0.78 1.38 0.137 1.10 0.568 0.80 1.51 0.601

Q3 0.92 0.524 0.71 1.19 0.96 0.767 0.71 1.28

Q4 1.00 0.975 0.75 1.34 1.22 0.232 0.88 1.68

Q5 0.68 0.043 0.47 0.99 0.73 0.126 0.48 1.09

ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.doi:10.1371/journal.pone.0096819.t010

Table 11. Impact of processes of stroke care on in-hospital mortality after all types of stroke.

OR P value 95% CI

Monitoring (%) 1.04 0.53 0.921.17

Early rehabilitation (%) 1.15 0.352 0.861.52

Admission to SCU (%) 0.87 0.039 0.760.99

Acute stroke team 0.88 0.029 0.790.99

Organized care index* 0.93 0.031 0.860.99

Existence of t-PA protocol (%) 0.88 0.295 0.691.12

Number of t-PA cases/year (mean) 1.00 0.203 0.991.00

Number of acute stroke patients/staff physician (mean) 0.999 0.012 0.9981.000

*The organized stroke care index was created to represent different levels of access to organized stroke care ranging from 0 to 3 as determined by the presence of earlyrehabilitation, acute stroke team assessment, and admission to a stroke unit based on the report of Saposnik et al. (2009).SCU, stroke care unit; t-PA, tissue plasminogen activator.doi:10.1371/journal.pone.0096819.t011



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Table 12. Impact of processes of stroke care on in-hospital mortality after ischemic stroke.

OR P value 95% CI

Monitoring (%) 0.98 0.738 0.851.12


Admission to SCU (%) 0.91 0.218 0.781.06

Acute stroke team 0.85 0.016 0.740.97Organized care index* 0.92 0.055 0.851.00





Table 13. Impact of processes of stroke care on in-hospital mortality after intracerebral hemorrhage.

OR P value 95% CI

Monitoring (%) 1.12 0.177 0.951.32


Hospitalization for SCU (%) 0.84 0.048 0.701.00







Table 14. Impact of processes of stroke care on in-hospital mortality after subarachnoid hemorrhage.

OR P value 95% CI

Monitoring (%) 1.04 0.737 0.841.28


Admission to SCU (%) 0.79 0.039 0.630.99









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patients in a real-world situation. The impact of this examination

on the mortality rates of this study would be difficult to evaluate

because of low usage. All 25 components of the questionnaire are

shown in the appendix. Second, discharge data obtained from the

Japanese DPC-based Payment System lacks important informa-

tion, such as post-discharge data and an NIHSS or GCS score as

an index of stroke severity at admission. Although the Japan Coma

Scale proved to be a powerful independent predictor of mortality

after all types of stroke, further study is necessary to validate theresults of the present study with another indicator of stroke

severity, such as the NIHSS or GCS. This can be done separately

or in combination with a validation data set (the estimated datavolume in the J-ASPECT 2013 is more than 80,000 cases that will

be available in 2013). Third, there is an inherent risk of

information bias when evaluating data obtained by self-assess-

ment. Moreover, hospitals actively working to improve stroke care

may have been more likely to respond to the questionnaire.

Admittedly, the participation rate of DPC data collection of the J-

ASPECT study was relatively low. The participation rates were

19.4% of the 1,369 certified training institutions of the Japan

Neurosurgical Society, and 35.4% of the 749 hospitals that

responded to the institutional survey. However, the institutes that

participated in the present study tended to have more beds and

more stroke cases than average. This suggests that the hospitalsthat were more active in stroke care and potentially eligible for

CSC participated in this study. Therefore, the present results may

not generalize to non-participating hospitals. External validation

greatly increases the reliability of self-assessment data. According-

ly, we plan to validate the information regarding hospital

characteristics and outcomes by using a small sample set from

the 2010 validation cohort of the present study. Since the number

of participating hospitals in this study is increasing every year, we

are planning to evaluate how the validity and reliability of the

CSC score in predicting stroke patient mortality changes when

weighting factors are applied to the recommended items, stroke

type, and severity. Through annual evaluations, we aim to achieve

higher predictive validity and responsiveness to establish the

usefulness of the CSC score. Fourth, we assigned 1 point if the

hospital met each recommended item for CSC. However, this

equal weight assumption is probably not valid since some

components were not significant on subgroup analysis. Although

some associations between individual CSC components and

mortality achieved significance, several did not but were very

close to significant, based on the confidence intervals. These non-

significant trends are telling and suggest that the subgroup

component analyses were underpowered and thus prone to type

2 error. In addition, we performed multiple comparisons for each

stroke type, and therefore, some of the secondary analyses,

particularly those that evaluated the impact of stroke care

procedures on in-hospital mortality, are prone to type 1 error.

We need a larger sample size to validate each recommended item

and appropriately weight the subscores.

Conclusions

Although patient demographics and stroke severity are impor-

tant predictors of in-hospital mortality of patients with all types of

stroke, CSC capacities were associated with reduced in-hospital

mortality rates, with relevant aspects of care dependent on stroke

type.

Supporting Information

File S1 English translation of the survey.

(DOCX)

File S2 List of the participating hospitals (J-ASPECT Study).

(DOCX)

Table S1 Japan Coma Scale for grading impaired consciousness.

(DOCX)

Table S2 The impact of total comprehensive stroke care (CSC)

score on in-hospital mortality after ischemic stroke adjusted by

age, sex, level of consciousness at admission, and incidence of

hypertension (HTN), diabetes mellitus(DM), and hyperlipide-mia(HPL).

(DOCX)


score on in-hospital mortality after intracerebral hemorrhage

adjusted by age, sex, level of consciousness at admission, andincidence of hypertension (HTN), diabetes mellitus(DM), and

hyperlipidemia(HPL).(DOCX)


score on in-hospital mortality after subarachnoid hemorrhage

adjusted by age, sex, level of consciousness at admission, and

incidence of hypertension (HTN), diabetes mellitus(DM), and

hyperlipidemia(HPL).

(DOCX)

Acknowledgments

The names of the participating 265 hospitals are listed in the File S2. Wethank Drs. Manabu Hasegawa, Shunichi Fukuhara, Hisae Mori, TakuroNakae, and Noriaki Iwata for their helpful discussions and Ms. ArisaIshitoko and Ai Shigemura for secretarial assistance.

Author Contributions

Conceived and designed the experiments: KI KN AK. Analyzed the data:KI KN AK. Wrote the paper: KI KN AK. Collection of data: JN KO JOYS TA S. Miyachi IN KT S. Matsuda YM AS KBI HK FN SK.

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